ENGLISH

Incomplete Information System and Rough Set Theory: Models and Attribute Reductions

By Jingyu Yang (auth.) , Xibei Yang

Book information

Publisher
Springer-Verlag Berlin Heidelberg
Year
2012
ISBN
978-3-642-25934-0, 978-3-642-25935-7
DOI
10.1007/978-3-642-25935-7
Language
english
Format
PDF
Filesize
2 MB (2383775 bytes)
Edition
1
Pages
232\237
Orientation
yes
Scanned
yes
Time added
2013-08-01 04:00:00
Data Mining and Knowledge Discovery; Models and Pr

Description

"Incomplete Information System and Rough Set Theory: Models and Attribute Reductions" covers theoretical study of generalizations of rough set model in various incomplete information systems. It discusses not only the regular attributes but also the criteria in the incomplete information systems. Based on different types of rough set models, the book presents the practical approaches to compute several reducts in terms of these models. The book is intended for researchers and postgraduate students in machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, and granular computing. Dr. Xibei Yang is a lecturer at the School of Computer Science and Engineering, Jiangsu University of Science and Technology, China; Jingyu Yang is a professor at the School of Computer Science, Nanjing University of Science and Technology, China.

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